"""记录参数"""
import torch
from torch import nn
forecast_steps = 18,
input_channels = 1,
out_channels=768,
num_context_steps=4,
context_channels = 768,
shape = (8,8,8),
num_timesteps = 8,
crop_size = 128,
num_layers_T = 3,
num_layers = 4
output_shape= 256,
gen_lr = 0.00005,
disc_lr = 0.0002,
visualize = False,
pretrained = False,
conv_type = "standard",
num_samples = 6,
grid_lambda = 20.0,
beta1 = 0.5,
beta2 = 0.999,
latent_channels = 768,
lr = 0.0002
lr_G = 0.0002
num_epoch = 600
batch_size =24
ngpu = 1
lamda = 20

#损失函数
criterion = nn.MSELoss() #均方损失函数
criterionl1 = nn.L1Loss()#学习分布而不是新生成
#criterionG = nn.BCELoss()
criterionG = nn.BCEWithLogitsLoss()
criterion_smooth = nn.SmoothL1Loss()